code: def check_install(logging_level: int = logging.INFO, **kwargs):
      config = {
          INPUT_FEATURES: [
              {"name": "in1", "type": "text"},
              {"name": "in2", "type": "category"},
              {"name": "in3", "type": "number"},
          ],
          OUTPUT_FEATURES: [{"name": "out1", "type": "binary"}],
          TRAINER: {"epochs": 2, "batch_size": 8},
      }
  
      try:
          df = build_synthetic_dataset_df(NUM_EXAMPLES, config)
          model = LudwigModel(config, logging_level=logging_level)
          with tempfile.TemporaryDirectory() as tmpdir:
              model.train(dataset=df, output_directory=tmpdir)
      except Exception:
          print("=== CHECK INSTALL COMPLETE... FAILURE ===")
          raise
  
      print("=== CHECK INSTALL COMPLETE... SUCCESS ===")
  
file_path: ludwig/ludwig/check.py
imports: import argparse
  import logging
  import tempfile
  from ludwig.api import LudwigModel
  from ludwig.api_annotations import DeveloperAPI
  from ludwig.constants import INPUT_FEATURES, OUTPUT_FEATURES, TRAINER
  from ludwig.data.dataset_synthesizer import build_synthetic_dataset_df
  from ludwig.globals import LUDWIG_VERSION
  from ludwig.utils.print_utils import get_logging_level_registry, print_ludwig
label_desc: Use image node_id 1 for calling a global function with example usage: check_install(logging_level) without return types